Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

IRTG1792DP2020 028

Tail Risk Network Effects in the Cryptocurrency Market during the COVID-19

Rui Ren
Michael Althof
Wolfgang Karl Härdle

Cryptocurrencies are gaining momentum in investor attention, are about to become
a new asset class, and may provide a hedging alternative against the risk of
devaluation of fiat currencies following the COVID-19 crisis. In order to
provide a thorough understanding of this new asset class, risk indicators need
to consider tail risk behaviour and the interdependencies between the
cryptocurrencies not only for risk management but also for portfolio
optimization. The tail risk network analysis framework proposed in the paper is
able to identify individual risk characteristics and capture spillover effect in
a network topology. Finally we construct tail event sensitive portfolios and
consequently test the performance during an unforeseen COVID-19 pandemic.

Cryptocurrencies, Network Dynamics, Portfolio Optimization, Quantile Regression,
Systemic Risk, Financial Risk Meter

JEL Classification: